• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.247-253
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• 2012

This paper presents sensor network based autonomous vehicle system using a proposed image processing algorithm. The proposed image processing algorithm consists of pre-processing and five-stage image processing: coordinate calculation, driving area decision, line segment calculation, steeling decision, and acceleration decision. We evaluate the performance of the proposed algorithm on both straight road and curved road. Experimental results indicate that the proposed algorithm works well for autonomous vehicles. However, control accuracy of the proposed algorithm decreases as speed is increasing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.796-804
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• 2002

This paper presents a new algorithm of fingerprint image analysis and processing using directional filter bank(DFB). The directional components of ridge is very important in pre-processing steps of fingerprint image processing such as image enhancement by directional filtering followed by estimationg the directional image of ridge patterns. The DFB analyzes input image into directional subband images and synthesizes them to the perfectly reconstructed image. In this paper, a new fingerprint processing algorithm using the DFB is proposed. The algorithm decomposes the fingerprint image into directional subband images and performs directional map generation, foreground segmentation, singular points extraction and image enhancement based on local directional energy estimate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4866-4888
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• 2020

One major and time-consuming task in fish production is obtaining an accurate estimate of the number of fish produced. In most Nigerian farms, fish counting is performed manually. Digital image processing (DIP) is an inexpensive solution, but its accuracy is affected by noise, overlapping fish, and interfering objects. This study developed a catfish recognition and counting algorithm that introduces detection before counting and consists of six steps: image acquisition, pre-processing, segmentation, feature extraction, recognition, and counting. Images were acquired and pre-processed. The segmentation was performed by applying three methods: image binarization using Otsu thresholding, morphological operations using fill hole, dilation, and opening operations, and boundary segmentation using edge detection. The boundary features were extracted using a chain code algorithm and Fourier descriptors (CH-FD), which were used to train an artificial neural network (ANN) to perform the recognition. The new counting approach, based on the geometry of the fish, was applied to determine the number of fish and was found to be suitable for counting fish of any size and handling overlap. The accuracies of the segmentation algorithm, boundary pixel and Fourier descriptors (BD-FD), and the proposed CH-FD method were 90.34%, 96.6%, and 100% respectively. The proposed counting algorithm demonstrated 100% accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.557-560
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• 2023

In this paper, we introduce a pre-training method leveraging the capabilities of the Vision Transformer (ViT) for disease diagnosis in conventional Fundus images. Recognizing the need for effective representation learning in medical images, our method combines the Vision Transformer with a Masked Autoencoder to generate meaningful and pertinent image augmentations. During pre-training, the Masked Autoencoder produces an altered version of the original image, which serves as a positive pair. The Vision Transformer then employs contrastive learning techniques with this image pair to refine its weight parameters. Our experiments demonstrate that this dual-model approach harnesses the strengths of both the ViT and the Masked Autoencoder, resulting in robust and clinically relevant feature embeddings. Preliminary results suggest significant improvements in diagnostic accuracy, underscoring the potential of our methodology in enhancing automated disease diagnosis in fundus imaging.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.359-360
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• 2021

The pixel-based processing of an image refers to a process of converting a value of one pixel only depending on the value of the current pixel, regardless of the value of another pixel. Pixel-based processing is used as the most basic operation in many fields such as image conversion, image enhancement, and image synthesis. There are processing methods such as arithmetic operation, histogram smoothing, and contrast stretching. In this paper, in order to clearly distinguish the tidal flat region from the tidal flat image of the west coast taken with a drone, we seek a method to find an efficient outline using pixel-based processing in the boundary detection part of the pre-processing process.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.235-245
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• 2018

Recently panoramic image overcomes camera limited viewing angle and offers wide viewing angle by stitching plenty of images. In this paper, we propose pre-processing and post-processing algorithm which makes speed and accuracy improvements when making panoramic images. In pre-processing, we can get camera sensor information and use three-dimensional rotation angle to find RoI(Region of Interest) image. Finding RoI images can reduce time when extracting feature point. In post-processing, we propose weighted minimal error boundary cut blending algorithm to improve accuracy. This paper explains our algorithm and shows experimental results comparing with existing algorithms.

• Imaging Science in Dentistry
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• v.48 no.4
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• pp.261-268
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• 2018

Purpose: To determine the impact of an image processing technique on diagnostic accuracy of digital panoramic radiographs for the assessment of anatomical structures in paediatric patients with mixed dentition. Materials and Methods: The study consisted of 50 digital panoramic radiographs of children aged from 6 to 12 years, which were later on processed using a dedicated image processing method. A modified clinical image quality evaluation chart was used to evaluate the diagnostic accuracy of anatomical structures in maxillary and mandibular anterior and maxillary premolar region of processed images. Results: A statistically significant difference was observed between pre and post-processed evaluation of anatomical structures(P<0.05) in the maxillary and mandibular anterior region. The anterior region was found to be more accurate in post-processed images. No significant difference was observed in the maxillary premolar region (P>0.05). The Inter-observer and intra-observer reliability of both pre and post processed images were excellent (>0.82) for anterior region and good (>0.63) for premolar region. Conclusion: The application of image processing technique in digital panoramic radiography can be considered a reliable method for improving the quality of anatomical structures in paediatric patients with mixed dentition.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.2
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• pp.128-134
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• 2014

Infrared thermography is an emerging approach to non-contact, non-intrusive, and non-destructive inspection of various solid materials such as metals, composites, and semiconductors for industrial and research interests. In this study, data processing was applied to infrared thermography measurements to detect defects in metals that were widely used in industrial fields. When analyzing experimental data from infrared thermographic testing, raw images were often not appropriate. Thus, various data analysis methods were used at the pre-processing and processing levels in data processing programs for quantitative analysis of defect detection and characterization; these increased the infrared non-destructive testing capabilities since subtle defects signature became apparent. A 3D finite element simulation was performed to verify and analyze the data obtained from both the experiment and the image processing techniques.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.417-426
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• 2023

To improve the effect of image restoration and solve the image detail loss, an image dehazing enhancement algorithm based on mean guided filtering is proposed. The superpixel calculation method is used to pre-segment the original foggy image to obtain different sub-regions. The Ncut algorithm is used to segment the original image, and it outputs the segmented image until there is no more region merging in the image. By means of the mean-guided filtering method, the minimum value is selected as the value of the current pixel point in the local small block of the dark image, and the dark primary color image is obtained, and its transmittance is calculated to obtain the image edge detection result. According to the prior law of dark channel, a classic image dehazing enhancement model is established, and the model is combined with a median filter with low computational complexity to denoise the image in real time and maintain the jump of the mutation area to achieve image dehazing enhancement. The experimental results show that the image dehazing and enhancement effect of the proposed algorithm has obvious advantages, can retain a large amount of image detail information, and the values of information entropy, peak signal-to-noise ratio, and structural similarity are high. The research innovatively combines a variety of methods to achieve image dehazing and improve the quality effect. Through segmentation, filtering, denoising and other operations, the image quality is effectively improved, which provides an important reference for the improvement of image processing technology.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.113-116
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• 1996

In this paper, an algorithm to generate the mounting position and orientation of SMD is proposed. For the proposed algorithm, we used the image captured from PCB and utilized image processing technique. Pre-processing technique, threshold level determination method, divided recognition of the SMD pattern on a PCB, calculating mounting position and orientation are related topics of this research. All of the related topics were reviewed and the results of this research were obtained from applying the algorithm to the real Surface Mounting Machine(model: MCU1 /CPM) made by Samsung Electronics Co.(Ltd.)